The direct comparison between MongoDB vs Couchbase shows that both databases are effective in many areas. If MongoDB scores points on flexibility, Couchbase is more suitable for real-time use.
MongoDB vs Couchbase: united in the NoSQL approach¶
Our MongoDB vs Couchbase comparison pits two of the most popular NoSQL databases against each other. This approach renounces, unlike traditional SQL, fixed and rigid table constellations and instead relies on a horizontal scalability. In most cases, NoSQL means “Not only SQL” because there are indeed points of contact with the approach that has long prevailed. The explosion in data volumes is forcing many users to turn to a database that is freely scalable but remains secure and clear.
Quick overview of MongoDB¶
Since its first release in 2009, MongoDB has become one of the most used database management systems for structured, semi-structured and unstructured data. The NoSQL database from MongoDB Inc. (formerly 10gen) uses a non-relational, document-oriented data model which is therefore very scalable. MongoDB is an open source solution offered by the Server Side Public License in free and proprietary licenses. The system uses the BSON format for storing recorded data, a binary form of JavaScript Object Notation (JSON). The query is done using MQL (MongoDB Query Language). MongoDB is written in C++ and many companies use it.
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What is Couchbase?¶
Couchbase was originally developed under the name Membase as an open source document-oriented NoSQL database. The software works in a decentralized manner and evolves both horizontally and vertically. The Couchbase database released in 2010 is written in C++, Erlang, C, Go and Java. The query language used is SQL++. The data is deposited in JSON documents and the focus is mainly on the interactive aspect.
Scope of use and scalability¶
In the foreground, the comparison between MongoDB vs Couchbase is between two NoSQL databases. Both solutions stand out for their high scalability: the fact that MongoDB does not use tables and also manages unstructured data allows very flexible use. This also allows scalability of large or increasing amounts of data. This system is therefore particularly suitable when the volume is not predictable in advance. Users, however, must learn a new query method for using MongoDB.
In the meantime, Couchbase has become a very popular solution in the field of interactive uses. The main reason lies in the excessively fast reaction speed during read and write requests, which reduces latency decisively. Couchbase is a Cloud-oriented solution, it is in fact very attractive for companies in other sectors. In our MongoDB vs Couchbase comparison, the slightly younger option can also compete well in the area of flexibility.
Just like MongoDB, Couchbase relies on CRUD operations (Create, Read, Update, Delete) but has an integrated admin console which makes use much easier. MongoDB configuration is done manually.
Operating mode¶
MongoDB stores and processes data in BSON format. These are thus created in documents which can in turn be grouped and consulted in collections. Multiple collections can be stored in a database. The combination of database and collection is called “Namespace”. Documents differ from a SQL system approach primarily because they can contain different types of data. They consist of key-value pairs even if the key is always a string. The values are often Boolean values, other documents, data or even strings of characters. The text index allows you to explore collections.
Like its competitors, the MongoDB vs Couchbase comparison shows that the second solution is based on the document as a basis. This is stored in format JSON (JavaScript Object Notation) without a predefined scheme. Storage is done on a hard drive or in RAM, although the second option considerably reduces reaction time. Querying and manipulating documents is done using SQL++'s own language (formerly N1QL) which draws heavily on classic SQL. It uses simple commands such as Delete, Insert, Merge, Select or Update. The query performance is comparatively higher.
Query Methods¶
The differences between MongoDB vs Couchbase are particularly evident in queries in the language concerned. Let's take the example of an employee register. We want to add new employee Marie Durand.
In MongoDB it would look like this:
db.employé.insertOne (
{
Prénom : "Marie",
Nom : "Durand"
Ville : "Paris"
Domaine : "IT"
}
)
mql
In Couchbase, the operation would look like this:
INSERT INTO employé (KEY, VALUE)
VALUES ( "1328",
{ "prénom" : "Marie",
"nom" : "Dupont",
"ville" : "Paris",
"domaine" : "IT"
} )
RETURNING *;
sql++
Architecture and availability¶
From an architecture and availability perspective, MongoDB vs Couchbase are distancing themselves again. Certainly, both distribute the load across different server nodes, which helps prevent possible outages. MongoDB is based on a model with a primary node and many subordinate nodes. Writes are directed to this master node, then are replicated. If the master node fails, a new one takes over. This may take up to 60 seconds. Couchbase uses different nodes which each consist of an index service, a data service, a query service, and a cluster manager component. This manager takes care of, among other things, replications and failover to another node.
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Compatibility and programming languages¶
Both Couchbase and MongoDB are compatible with different server operating systems. Both databases work with Linux, macOS and Windows. MongoDB also works with Solaris.
In the MongoDB vs Couchbase match, MongoDB scores points on programming languages as the list of supported languages shows us:
Programming language | Backed by MongoDB | Supported by Couchbase |
---|---|---|
Actionscript | ✓ | ✗ |
VS | ✓ | ✓ |
VS# | ✓ | ✗ |
C++ | ✓ | ✗ |
Clojure | ✓ | ✗ |
ColdFusion | ✓ | ✗ |
D | ✓ | ✗ |
Dart | ✓ | ✗ |
Delphi | ✓ | ✗ |
Erlang | ✓ | ✗ |
Go | ✓ | ✓ |
Groovy | ✓ | ✗ |
Haskell | ✓ | ✗ |
Java | ✓ | ✓ |
JavaScript | ✓ | ✓ |
Kotlin | ✓ | ✓ |
Lisp | ✓ | ✗ |
Lua | ✓ | ✗ |
MatLab | ✓ | ✗ |
.net | ✗ | ✓ |
Perl | ✓ | ✗ |
PHP | ✓ | ✓ |
PowerShell | ✓ | ✗ |
Prolog | ✓ | ✗ |
Python | ✓ | ✓ |
R | ✓ | ✗ |
Ruby | ✓ | ✓ |
Scala | ✓ | ✓ |
Smalltalk | ✓ | ✗ |
Swift | ✓ | ✗ |
Security¶
Regarding data security at MongoDB vs Couchbase, it all depends on the edition that users have. Free options only offer primary safety functions and require additional manual security measures to be taken. So, the standard version of MongoDB does not offer any preconfigured access controls. On the other hand, proprietary licenses provide numerous security mechanisms. MongoDB Atlas offers, among other things, X.509, client- and server-side encryption, and Kerberos and LDAP integration.
Couchbase can also encrypt, allows user authentication, allows role assignment, and monitors the database. Additional security measures, such as the use of a firewall, remain absolutely essential.
Mobile version¶
In our MongoDB vs Couchbase duel, both solutions offer additional options for mobile use. MongoDB Realm is designed for a mobile operating system and MongoDB Atlas has strategies in the use of mobile systems. Couchbase Mobile can be used on all possible devices and is designed for decentralized and secure use Edge to Cloud. The corresponding database is optimized for mobile software distribution and embedded systems.
MongoDB vs Couchbase: Which Companies Use MongoDB or Couchbase?¶
Large and well-known companies use MongoDB and Couchbase for a variety of purposes.
The most famous companies that use MongoDB are:
- Adobe
- Amadeus
- AppScale
- Craftbase
- Disney
- Etsy
- Foursquare
- Lyft
- MTV
- The New York Times
- Via Varejo
The following companies use Couchbase in part or in full:
- Amadeus
- AT&T
- Cisco
- Disney
- DreamWorks
- eBay
- Marriott
- Office Depot
- Salesforce
- Tommy Hilfiger
- Verizon